Results 241 to 250 of about 49,392 (306)

Phenotype imputation using high‐throughput phenotyping produces a new secondary trait for further selection modeling

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Data from high‐throughput phenotyping (HTP) could be used for phenotype imputation to enhance genomic selection (GS) or gene discovery, but this has not been explored in crop species. Three machine learning models: multiple linear regression (MLR), missForest, and k‐nearest neighbors, were evaluated for grain yield (GY) phenotype imputation in
Raysa Gevartosky   +2 more
wiley   +1 more source

First Analysis and Experiments in Aerial Manipulation Using fully Actuated Redundant Robot Arm.

open access: yes, 2013
Dominik Sommer   +19 more
core   +1 more source

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal   +8 more
wiley   +1 more source

AGIcam: An open‐source Internet of Things–based camera system for automated in‐field phenotyping and yield prediction

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Continuous, high‐frequency monitoring is essential to capture rapid phenological transitions and dynamic crop responses to the environment. However, most phenotyping platforms lack the temporal resolution and automation required for consistent, season‐long trait assessment.
Worasit Sangjan   +5 more
wiley   +1 more source

A reliable unmanned aerial vehicle multi-ship tracking method. [PDF]

open access: yesPLoS One
Zhang G   +7 more
europepmc   +1 more source

Automatic measurement of rice tiller angle from unmanned aerial vehicle images

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Rice (Oryza sativa L.) tiller angle is an important trait that influences plant architecture, canopy light interception, and yield potential. In this study, we proposed a deep learning‐based pipeline for automated measurement of rice tiller angle and plant base width using unmanned aerial vehicle (UAV) imagery.
Tan‐Hanh Pham   +10 more
wiley   +1 more source

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